Constructing a Mimicking Soccer Agent Using Neural Networks

Naoki Namikawa; Tomoharu Nakashima; Hisao Ishibuchi

doi:10.14864/softscis.2006.0.69.0

SCIS & ISIS 2006

Session ID : TH-D2-3

DOI https://doi.org/10.14864/softscis.2006.0.69.0

Conference information

Host: Japan SOciety for Fuzzy Theory and intelligent informatics

Co-host: The Korea Fuzzy Logic and Intelligent Systems Society, IEEE Computational Intelligence Society, The International Fuzzy Systems Association, 21th Century COE Program "Creation of Agent-Based Social Systems Sciences"

TH-D2 RoboCup Soccer

Constructing a Mimicking Soccer Agent Using Neural Networks

*Naoki Namikawa, Tomoharu Nakashima, Hisao Ishibuchi

Author information

Keywords: RoboCup soccer, Neural Network, Observational learning

CONFERENCE PROCEEDINGS FREE ACCESS

Details

Abstract

This paper proposes a framework for acquiring a low-level behavior of a soccer agent. The task of a learning agent is to mimic the behavior of a target agent with a well-trained behavior. Neural networks are used to represent the behavior of the target agent. In order to obtain a set of training data, we convert game logs of the target agent into a set of input-output pairs for the neural networks. We show the effectiveness of the proposed framework through the computational experiments.

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